一种基于在线评论共现特征词的舆情事件相关度计算方法

An Evaluation Method of Relative Intensity of Online Public Opinion Based on Co-occurrence Feature Word

从在线评论文本内容出发,抽取事件评论中的共现特征词集合,提出了一种基于共现特征词的网络舆情相关度计算方法,并和传统的计算方法进行比较。利用"郭美美事件"、"李刚之子事件"和"李天一事件"等六大网络舆情热点事件作为案例,并结合搜索引擎关注度对相关度在网络舆情事件波及影响方面进行分析。结果表明,该算法能更有效度量舆情之间的相关程度,为网络舆情中相关事件波及影响分析提供了依据。

From perspective of online comments, this paper extracted the co-occurrence feature word of the event comments, and put forward a calculation method of correlation intensity of online public opinion based on co-occurrence feature words. This study selected the six hot public events as the study case, and combined with search engine visibility to verify the model. The results showed that the algorithm can effectively measure the degree of correlation between public opinions and provides a basis for the impact analysis of online public opinion related events.